The combined use of dynamic factor analysis and wavelet analysis to evaluate latent factors controlling complex groundwater level fluctuations in a riverside alluvial aquifer

摘要

Highlights?Complex groundwater level fluctuations in a riverside alluvial aquifer were examined.?Coupled DFA and WA was developed to separate latent driving forces.?The efficiency of DFA was improved by wavelet based clustering.?MRCCA and WTC analyses were used to quantify major driving forces.AbstractTo identify and quantitatively evaluate complex latent factors controlling groundwater level (GWL) fluctuations in a riverside alluvial aquifer influenced by barrage construction, we developed the combined use of dynamic factor analysis (DFA) and wavelet analysis (WA). Time series data of GWL, river water level and precipitation were collected for 3?years (July 2012 to June 2015) from an alluvial aquifer underneath an agricultural area of the Nakdong river basin, South Korea. Based on the wavelet coefficients of the final approximation, the GWL data was clustered into three groups (WCG1 to WCG3). Two dynamic factors